论文信息 - Automated fixed-point precision optimization

Automated fixed-point precision optimization

An algorithm which minimizes the hardware resources of fixed-point operations for a given accuracy is presented. For range analysis, forward propagation is used in order to determine the ranges of the intermediate signals. For the precision analysis, a search algorithm is used. Analytical quantization error models are used with the precision search algorithm. The main novelty of this work is the use of the weighted search algorithm which can minimize the hardware resources for a specific FPGA. By using weights, the search algorithm is modified to produce an optimum result for the target FPGA for a specific hardware resource such as multipliers or blok rams.

Ömer Özdil | Alper Yildirim | Mehmet Ispir | Emrah Onat

[1] Sanghamitra Roy,et al. An algorithm for trading off quantization error with hardware resources for MATLAB-based FPGA design , 2005, IEEE Transactions on Computers.

[2] Bruce F. Cockburn,et al. A Unified Architecture for the Accurate and High-Throughput Implementation of Six Key Elementary Functions , 2010, IEEE Transactions on Computers.

[3] Wayne Luk,et al. Ieee Transactions on Computer-aided Design of Integrated Circuits and Systems Accuracy Guaranteed Bit-width Optimization Abstract— We Present Minibit, an Automated Static Approach for Optimizing Bit-widths of Fixed-point Feedforward Designs with Guaranteed Accuracy. Methods to Minimize Both the In- , 2022 .

[4] Sanghamitra Roy,et al. An Algorithm for Trading Off Quantization Error with Hardware Resources for MATLAB-Based FPGA Design , 2005, IEEE Trans. Computers.